Removing microstates heavily attenuates the periodic (e.g., alpha power) and aperiodic (1/f offset and exponent) spectral features of the EEG. The dynamics of microstates and the global characteristics of the EEG power spectrum originate from a common brain network architecture.

We isolated and removed the spatial projections of distinct microstates from high-density resting EEG at the source- and sensor-levels using orthogonal subspace projection and examined the resultant reduction in periodic rhythms and aperiodic 1/f characteristics in the residual signal.

Attention depends on the dynamics of transient, millisecond brain states. Microstate E actively supports attention maintenance, while microstate C is linked to lapses over longer timescales, heavily influencing alpha rhythms. Source localization corroborates these functions.

Are microstates responsible for classic attention-related prestimulus effects in the alpha band? Yes! Microstate C had the strongest coincident alpha power and dominated within alpha oscillatory episodes, suggesting its brain generators are primarily responsible for these effects

What about over the entire task session? As time-on-task progressed and cognitive demand accumulated across the 30+ minute session, microstate C increased in prevalence. This mirrored subjective reports: focus declined and task-unrelated thoughts (TUTs) increased.

On longer wait time delays, as attention struggled to be maintained, Microstate E systematically increased in occurrence rate and duration. We interpret this as reflecting systems that have to work harder to maintain attention during longer wait time delays.

We isolated endogenous attention in the wait time delay of trials using a modified Sustained Attention to Cue Task (SACT). Participants maintained attention on a cued spatial location for variable wait time delays (0 to 40 seconds) while we recorded 128-channel EEG.

These same microstates were also implicated in the maintenance of attention over short and long timescales, with their time-varying dynamics changing systematically during the wait time delay of trials and over the course of the task session.

We segmented the EEG in the wait time delay of trials into microstates and categorized the original time series according to the global microstate topographies.

We recorded 128-channel EEG while participants maintained their attention during the wait time delay of trials in the Sustained Attention to Cue Task (SACT; see rdcu.be/fbbIP).